Posts List

Retrieval Augmented Generation (RAG) with Vertex AI and Langchain

Implementing Retrieval Augmented Generation (RAG) is like having an AI assistant with a vast library of knowledge at its fingertips. It seamlessly blends the precision of retrieval-based models with the creativity of generative models. Picture this: instead of conjuring content out of thin air, RAG sifts through a treasure trove of data to craft insightful, contextually relevant outputs.

What is Explainable AI โ€” Permutation Feature Importance using Tensorflow

How do we trust that AI is making good decisions? How do we affirm the decisions of our typical deep neural networks? How can AI explain itself?

Solving for Inclusion in Machine Learning

Machine learning has become increasingly prevalent in many areas of our lives, from recommending products to us on shopping websites, to determining who gets hired for a job.

Introduction to Modern Reinforcement Learning

Sometime last year, I stumbled upon a paper while I was trying to come up with a really basic way to implement a budget and expenditure planner using an RL agent.

Different Real Life Use-cases of Tensorflow

TensorFlow is one of the most widely and well known tools for machine learning and with its various features, it maintains its versatility to operate in different use cases.

Image Classification with Google Cloud AutoML Vision

Google Cloud AutoML is pretty cool, in that it allows developers to easily train custom machine learning models for vision, natural language, and translation without writing model code.

The Importance of One-hot Encoding in Machine Learning

The idea of one-hot encoding labels in supervised learning isnโ€™t really new. The need for encoding categorical data birthed out of a necessity for data science and machine learning algorithms to understand categorical data.

Getting Started With TensorFlow โ€“ (The Flow of Tensors)

TensorFlow is a machine learning library used to implement deep learning algorithms in Python, and is very popular for being the most generally used machine learning framework by researchers and industry experts.

Linear Algebra for Machine Learning (4 of 4) โ€“ (The Flow of Tensors)

In this final and 4th Part of our brief look into Linear Algebra, weโ€™ll talk about the Transpose and Inverse of matrices.

Linear Algebra for Machine Learning (3 of 4) โ€“ (The Flow of Tensors)

Hereโ€™s the Part 3 of our brief look into Linear Algebra, and weโ€™ll learn about matrix-vector multiplication, matrix-matrix multiplication, as well as some essential matrix multiplication properties to note.

Linear Algebra for Machine Learning (2 of 4) โ€“ (The Flow of Tensors)

In this Part 2 of our brief look into Linear Algebra, weโ€™ll learn about matrix addition and subtraction, as well as matrix-scalar multiplication.

Linear Algebra for Machine Learning (1 of 4) โ€“ (The Flow of Tensors)

The goal for โ€œThe Flow of Tensorsโ€ series is to allow us understand how to build machine learning apps using the popular TensorFlow library. But the journey of every traveller always has a beginning. And for this journey, our beginning is a small part of mathematics known as Linear Algebra.

What AutoML Really Is

Machine Learning in itself is a set of methodologies and techniques that take datasets and turn them into (smart) software called models.

Face Detection With Mobile Vision API in Android

When the last Face Detection library came out with the actual Mobile Vision API in Android, it was said to be designed to detect faces even at different orientations, at specific landmarks such as the eyes, the nose, and the edges of the lips.

Learning and Teaching ML to The Immediate (Nigerian) Developer Communityโ€Š โ€” โ€ŠThe Journey Soย Far?

Up until this very moment, nothing in the world has sparked my interest as much as Artificial Intelligence had, and for as long as I can remember, Iโ€™ve desperately wanted to plug myself into the journey of bridging the gap between human intelligence and computer intelligence.

What Machine Learning Is โ€” Very Simply Put

Machine learning is an interesting technology, and it is rapidly becoming an integral part of (almost) all AI systems.